Edge Traversals¶

This guide covers navigating relationships between vertices using Gremlin traversal steps.

Vertex-to-Vertex Steps¶

These steps traverse edges and return the adjacent vertices:

// Outgoing neighbors (follow outgoing edges)
g.V().has('name', 'Alice').out('KNOWS')

// Incoming neighbors (follow incoming edges)
g.V().has('name', 'Bob').in('KNOWS')

// Both directions
g.V().has('name', 'Alice').both('KNOWS')

Without Edge Label¶

Omit the label to traverse all edge types:

// All outgoing neighbors regardless of edge type
g.V().has('name', 'Alice').out()

// All incoming neighbors
g.V().has('name', 'Alice').in()

// All neighbors in both directions
g.V().has('name', 'Alice').both()

Vertex-to-Edge Steps¶

These steps return the edge elements themselves, not the adjacent vertices:

// Outgoing edges
g.V().has('name', 'Alice').outE('KNOWS')

// Incoming edges
g.V().has('name', 'Bob').inE('KNOWS')

// Edges in both directions
g.V().has('name', 'Alice').bothE('KNOWS')

Accessing Edge Properties¶

Once you have edges, you can access their properties:

// Get the 'since' property of outgoing KNOWS edges
g.V().has('name', 'Alice').outE('KNOWS').values('since')

Edge-to-Vertex Steps¶

When traversing edges, use these steps to reach the connected vertices:

// Source vertex of an edge
g.V().has('name', 'Alice').outE('KNOWS').outV()

// Target vertex of an edge
g.V().has('name', 'Alice').outE('KNOWS').inV()

// Both endpoints
g.V().has('name', 'Alice').outE('KNOWS').bothV()

// The "other" vertex (not the one you came from)
g.V().has('name', 'Alice').outE('KNOWS').otherV()

Chaining Traversals¶

Chain multiple steps for multi-hop traversals:

// Friends of friends
g.V().has('name', 'Alice').out('KNOWS').out('KNOWS')

// Friends of friends (unique)
g.V().has('name', 'Alice').out('KNOWS').out('KNOWS').dedup()

// People who work at companies Alice's friends work at
g.V().has('name', 'Alice')
    .out('KNOWS')
    .out('WORKS_AT')
    .in('WORKS_AT')
    .dedup()

Filtering During Traversal¶

Combine traversal with filter steps:

// Friends of Alice who are over 30
g.V().has('name', 'Alice').out('KNOWS').has('age', P.gt(30))

// Outgoing KNOWS edges created after 2020
g.V().has('name', 'Alice').outE('KNOWS').has('since', P.gt(2020)).inV()

Python Example¶

import grafeo

db = grafeo.GrafeoDB()

# Create a social graph
db.execute("INSERT (:Person {name: 'Alice', age: 30})")
db.execute("INSERT (:Person {name: 'Bob', age: 25})")
db.execute("INSERT (:Person {name: 'Charlie', age: 35})")
db.execute("""
    MATCH (a:Person {name: 'Alice'}), (b:Person {name: 'Bob'})
    INSERT (a)-[:KNOWS {since: 2020}]->(b)
""")
db.execute("""
    MATCH (b:Person {name: 'Bob'}), (c:Person {name: 'Charlie'})
    INSERT (b)-[:KNOWS {since: 2021}]->(c)
""")

# Direct friends
friends = db.execute_gremlin("g.V().has('name', 'Alice').out('KNOWS').values('name')")
for row in friends:
    print(row)  # Bob

# Friends of friends
fof = db.execute_gremlin(
    "g.V().has('name', 'Alice').out('KNOWS').out('KNOWS').values('name')"
)
for row in fof:
    print(row)  # Charlie

Step Reference¶

Step	From	Returns	Description
`out(label?)`	Vertex	Vertices	Outgoing adjacent vertices
`in(label?)`	Vertex	Vertices	Incoming adjacent vertices
`both(label?)`	Vertex	Vertices	Adjacent vertices in both directions
`outE(label?)`	Vertex	Edges	Outgoing edges
`inE(label?)`	Vertex	Edges	Incoming edges
`bothE(label?)`	Vertex	Edges	Edges in both directions
`outV()`	Edge	Vertex	Source vertex of edge
`inV()`	Edge	Vertex	Target vertex of edge
`bothV()`	Edge	Vertices	Both endpoints of edge
`otherV()`	Edge	Vertex	The opposite endpoint